Thesis

Why Don't Chinese Girls Choose Prestigious Universties (On-going),  work with: Yi Chen (ShanghaiTech University),  Sikun Dou(ShanghaiTech University), and Hongbin Li(Stanford University)

Abstract:  We observe a longstanding phenomenon in China over the past two decades: the declining representation of women as they advance through the university hierarchy. Our analysis, based on administrative data from China’s college entrance exams spanning from 1999 to 2003, reveals compelling evidence that even when Chinese girls achieve the same scores as their male counterparts, they are less likely to attend elite universities (Project 985). The tradeoff is that they are less likely to fail their target universities. We identify two key explanations for this phenomenon. First, elite universities in China disproportionally focus on science and technology, resulting in a smaller share of female students. Second, when confronted with high-stakes and high-risk decisions, such as choosing a university, girls tend to make conservative choices. This is particularly important because, during the early 2000s, most Chinese provinces adopted a sequential admission mechanism. Choosing the first-choice school became a critical and risky decision. If a student’s exam score barely misses the admission cutoff for their first-choice school, they could end up in a considerably less desirable institution. Supporting our findings, we exploit a reform that shifted the timing of school submissions from before the exam to after the exam. This change reduced uncertainties and subsequently helped narrow the gender.

The impact of artificial intelligence on the gender equality in the labor market in China. Supervisor: Professor Sebastian Kube.

Abstract:  This study investigates the effect of artificial intelligence on gender equality(unemployment risk gap, the wage gap, glass ceiling, and sticky floor) in China’s labor market. The main contribution of this thesis is to develop a method, by using some indicators to distinguish humanity and artificial intelligence, to measure exposure scores of occupations under the application of artificial intelligence. For empirical analysis, the Ordinary Least Squares and Conditional Quantile Regression models are applied to explore the relationship between annual wage and exposure score. The study finds that females are more exposed to the higher unemployment risk of artificial intelligence. Also, the gender gap in wages would expand. In addition, there exist heterogeneous impacts of artificial intelligence on gender inequality due to the uneven geographical distribution of occupations in China. Results suggest that policymakers need to address structural reform in the labor market, develop preferential policies for female workers, and strengthen women’s capacity building in the artificial intelligence era to mitigate unequal risk of unemployment between genders.

Pure Environmentalism?  Not Really Carbon Taxation’s Social Welfare Effects in Germany, with Zhiqiang Zhang and Shanshan Song. Supervisors: Professor Moritz Kuhn and Junior Professor Pavel Brendler.

Abstract: The paper examines the non-environmental welfare effect of carbon taxation in Germany. In this paper, the Overlapping Generation Model is applied to measure the welfare effects on the younger generations and older households under the carbon taxation policy. Three experiments are conducted: nocarbon taxation,carbon taxation without rebate and with rebate. From the view of social efficiency and equity, the non-environmental welfare effects of the carbon taxation in Germany are quantified such that we find that carbon taxation improves the welfare of younger generation greater than older generation, for newborn generation agents, they prefer living with carbon taxation reform. Thus, carbon taxation is basically regarded  as a good choice for Germany to improve both environmental and social welfare.

Research on the impact of exhibition venues on the development of the tertiary industry, taking Shanghai as a case study. Supervisors: Professor Peter Mayer and Dr. Ye Ding.

Abstract: In the background of rapid development of exhibition venues and the tertiary industry, there arouses the discussion about how and to what extent exhibition venues affect the development of the tertiary industry. This thesis aims to research into relationship between them through the method of case study, empirical analysis and grey relevance analysis. The research finds that exhibition venues do have significant impact on the tertiary industry through the approach of industrial relevance. Furthermore, exhibition venues are closely associated with the sub-industries of the tertiary industry such as resident service and other service and culture, sports and entertainment.